亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Detection of common risk factors for diagnosis of cardiac arrhythmia using machine learning algorithm

心律失常 计算机科学 人工智能 机器学习 算法 内科学 医学 心房颤动
作者
Samir S. Yadav,Shivajirao M. Jadhav
出处
期刊:Expert Systems With Applications [Elsevier BV]
卷期号:163: 113807-113807 被引量:42
标识
DOI:10.1016/j.eswa.2020.113807
摘要

This article aims to establish an accurate and innovative objective framework for classification of cardiac arrhythmia patients by trying to measure the importance of specific factors that are potentially relevant to its diagnosis. Cardiac arrhythmia (CA) is a group of condition related to the irregular heartbeats. It is very essential to prevent a CAs, as they are the most common cause of natural death in all over the world. According to the health reports, more than 4.5 lakh cardiac patients fatalities annually in the United States alone. To diagnose cardiac diseases, patient’s reported qualitative symptoms can be useful. However, this strategy may fail sometimes due to less accuracy and false positive cases. Therefore in this work, we strive to find a quantitative basis for more reliable and accurate diagnosis of cardiac arrhythmias. This research used the openly available MIMIC-III database to obtain large quantities of clinical monitoring data from patients over the age of sixteen admitted to intensive care units (ICUs). The database was processed on the Health Sciences and Technology (HEST) Cluster, filtered with in a specified time frame(24hrs, 12hrs and 6hrs) and organized into a multi-class and a single-class and finally split into train, validation, and test sets with respective weights of 0.7, 0.2, and 0.1. We used random forest classifier model for the diagnosis of cardiac arrhythmia and measure the importance of different features like respiratory rate, blood pressure, sodium, potassium, calcium, among the other features. Hyperparameter optimization techniques like grid search and genetic algorithms are compared to find the maximum number and depth of trees in the forest. The model achieved, at its best, an Area Under the Receiver Operator Curve (AUC) score of 0.9787 and, thus, confirmed the importance of several previously suggested factors in the diagnosis of cardiac arrhythmias. We substantiated claims that each of sodium, calcium, potassium, respiratory rates and blood pressure can be used for the early diagnosis of cardiac arrhythmias.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
smile发布了新的文献求助10
刚刚
YJL完成签到 ,获得积分10
2秒前
rrrred发布了新的文献求助10
6秒前
回眸完成签到 ,获得积分10
7秒前
Duduk完成签到 ,获得积分10
8秒前
9秒前
rrrred完成签到,获得积分10
13秒前
南宫连虎发布了新的文献求助10
15秒前
传奇3应助cc采纳,获得10
18秒前
38秒前
量子星尘发布了新的文献求助10
38秒前
longh发布了新的文献求助20
40秒前
cc发布了新的文献求助10
42秒前
aa发布了新的文献求助10
43秒前
lucky完成签到 ,获得积分10
44秒前
123完成签到,获得积分10
53秒前
54秒前
54秒前
fat完成签到,获得积分10
57秒前
123发布了新的文献求助10
58秒前
脑洞疼应助lf采纳,获得10
1分钟前
健壮的花瓣完成签到 ,获得积分10
1分钟前
oywt发布了新的文献求助10
1分钟前
霸气鞯完成签到 ,获得积分10
1分钟前
1分钟前
lf发布了新的文献求助10
1分钟前
1分钟前
1分钟前
1分钟前
bbdd2334发布了新的文献求助10
1分钟前
1分钟前
1分钟前
李健的小迷弟应助bbdd2334采纳,获得10
1分钟前
1分钟前
忧伤的风华完成签到,获得积分10
1分钟前
thanhvader999完成签到,获得积分10
1分钟前
小乘号子发布了新的文献求助10
1分钟前
量子星尘发布了新的文献求助10
1分钟前
1分钟前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 700
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3976600
求助须知:如何正确求助?哪些是违规求助? 3520700
关于积分的说明 11204482
捐赠科研通 3257320
什么是DOI,文献DOI怎么找? 1798683
邀请新用户注册赠送积分活动 877881
科研通“疑难数据库(出版商)”最低求助积分说明 806613